52 applicants

Company

Veeam Software · 6 hours ago

Machine Learning Engineer

California, United States

Full-time

Remote

Mid Level

$168K/yr - $240K/yr

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Cloud InfrastructureData Center

Comp. & Benefits

No H1B

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Responsibilities

Design, build, and refine machine learning models for diverse use cases, including ransomware detection, backup data classification, and conversational AI

Implement scalable and reproducible ML pipelines on Azure, using managed services such as Azure Fabric, Azure Machine Learning, Azure Data Lake Service, Azure Data Factory, Databricks, and/or Snowflake

Integrate models into production services and ensure robust monitoring, logging, and automated CI/CD (MLOps) practices for continuous improvement and rapid iteration

Collaborate with data engineers to define data architectures and managed services that facilitate efficient model training and inference

Continuously optimize ML models through feature selection, engineering, dimensionality reduction, and benchmarking to enhance accuracy, latency, and scalability

Implement model quality checks, bias detection, and model explainability frameworks to maintain ethical and transparent AI standards

Work closely with product managers, UX designers, and stakeholders to understand business requirements and translate them into technical ML solutions

Educate and mentor team members, data scientists, and engineers on ML best practices, frameworks, and toolsets

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Machine LearningPythonAzureMLOpsTensorFlowPyTorchScikit-learnDatabricksSnowflakeDockerKubernetesData LakeAnomaly DetectionTime Series AnalysisNatural Language ProcessingStatistical Knowledge

Required

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Data Science, Machine Learning, or a related field

Proven experience building and deploying ML models in production using Python and popular ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn)

Hands-on experience with modern ML tools and services, including Azure Fabric, Azure ML Studio, Azure Data Lake, Databricks, Snowflake, and similar services

Strong knowledge of MLOps principles, data governance best-practices, CI/CD pipelines, containerization (Docker), orchestration (Kubernetes), and networking

Familiarity with anomaly detection, time series analysis, and/or NLP

Strong statistical knowledge, including hypothesis testing, regression analysis, and model evaluation metrics

Ability to deconstruct a broad problem or ask into smaller well-defined components. Identify and flesh out uncertainty where needed

Excellent communication and interpersonal skills, with the ability to explain complex ML concepts to both technical and non-technical stakeholders

Self-driven, detail-oriented, and excited about working in a dynamic, fast-paced, startup-like environment within a larger organization

Benefits

Medical, dental, and vision insurance. Employee premiums for health insurance are 100% company paid

Unlimited Paid Time Off

Life and Disability Insurance

Veeam Care Days – additional 24 hours for your volunteering activities

Professional training and education, including courses and workshops, internal meetups, and unlimited access to our online learning platforms (Percipio, Athena, O’Reilly) and mentoring through our MentorLab program